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Albumin Ratio, a Risk Factor for Postoperative Delirium in Elderly Patients After Total Joint Arthroplasty
The Journal of Arthroplasty xxx (2019) 1e5
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Preoperative C-Reactive Protein/Albumin Ratio, a Risk Factor for Postoperative Delirium in Elderly Patients After Total Joint Arthroplasty Jie Peng, MMBS, Guorong Wu, MMBS, Junping Chen, MMBS, Hui Chen, MMBS * Department of Anesthesiology, HwaMei Hospital, University of Chinese Academy of Sciences (Ningbo No.2 Hospital), Ningbo, Zhejiang Province, China
a r t i c l e i n f o
a b s t r a c t
Article history: Received 7 May 2019 Received in revised form 18 June 2019 Accepted 18 June 2019 Available online xxx
Background: Postoperative delirium (POD), as an acute brain failure, is widely reported as a very common postoperative complication, and it is closely associated with increased morbidity and mortality. This study aimed to investigate potential risk factors including C-reactive protein/albumin ratio (CAR) for POD in elderly subjects after total joint arthroplasty (TJA). Methods: A total of 272 elderly patients (aged 65~85 years) who were scheduled to undergo elective TJA with epidural anesthesia were consecutively recruited. The data of baseline characteristics, operationassociated indexes, and preoperative laboratory tests were collected. POD assessment was performed daily within postoperative 7 days. Receiver operating characteristic curve analysis was utilized for evaluating the predictive and cut-off value of CAR for POD. Risk factors for POD were evaluated by the binary univariate and multivariate logistic regression analyses. Results: Within postoperative 7 days, there were 55 patients who had suffered POD with an incidence of 20.2% (55/272). The area under the curve of CAR for POD was 0.804, with the cut-off value of 2.35, a sensitivity of 66.82%, and a specificity of 80.00%, respectively (95% confidence interval [CI]: 0.737-0.872, P < .001). Age (odds ratio: 2.02, 95% CI: 1.03-3.96, P ¼ .038) and preoperative CAR level (odds ratio: 3.04, 95% CI: 1.23-7.23, P ¼ .016) were 2 independent risk factors for POD in elderly subjects undergoing TJA. Conclusions: Preoperative CAR level may be a promising predictor for POD in elderly subjects following TJA. © 2019 Published by Elsevier Inc.
Keywords: total joint arthroplasty postoperative delirium C-reactive protein/albumin ratio risk factor biomarker
Postoperative delirium (POD), as an acute brain failure, is widely reported as a very common postoperative complication, and approximately, 50% of surgical patients have experienced POD [1].
Funding: The Key Program of Ningbo Natural Science Foundation, China (No. 2018A610216). Competing interests: None. Authors' contributions: J P and GR W participated in the conception and design, data collection, statistical analysis and wrote the manuscript. H C and JP C participated in the conception and design and data collection. No author associated with this paper has disclosed any potential or pertinent conflicts which may be perceived to have impending conflict with this work. For full disclosure statements refer to https://doi.org/10.1016/j.arth.2019.06.042. * Reprint requests: Hui Chen, MMBS, Department of Anesthesiology, HwaMei Hospital, University of Chinese Academy of Sciences (Ningbo No.2 Hospital), No.41 Xibei Road, Haishu District, Ningbo, Zhejiang Province, China. https://doi.org/10.1016/j.arth.2019.06.042 0883-5403/© 2019 Published by Elsevier Inc.
POD has become a crucial public health problem as it is closely associated with decreased life quality, prolonged hospital length of stay, increased morbidity, and mortality [2]. Numerous studies have demonstrated the detrimental impact of high POD severity on shortterm and long-term outcomes [3]. As described by previous studies, the incidence of POD varies from 15% to 53% in elderly surgical subjects [4]. A meta-analysis by Scott et al has revealed that the overall incidence of POD reaches as high as 17% in patients who underwent total joint arthroplasty (TJA) during hospital admission [5]. A prospective study by Chen et al has also reported a similar incidence of 16.5% after TJA [6]. However, the reported incidence of POD varies widely in different studies. Furthermore, to our knowledge, few wellestablished predictors have been outlined for POD incidence to date. Taken together, it is of great importance to determine potential independent risk factors for POD and risk stratification. C-reactive protein (CRP), an acute phase protein secreted by the liver and adipose tissue, is one of the most common biomarkers for
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systemic inflammation [7]. Some studies have indicated CRP as an independent risk factor for POD after hip surgery [8], vascular surgery, [9] and laparoscopic surgery for colon carcinoma [10]. Albumin (Alb), another circulating acute phase protein, is a frequently used parameter to assess the nutritional status of surgical patients [11]. Previous studies have shown that hypoalbuminemia is significantly associated with increased risks of postoperative complications including POD [12,13]. However, no consensus concerning the predictive role of CRP or Alb for POD has been made. The CRP/Alb ratio (CAR), a combination of CRP and Alb, has been suggested as a promising prognostic factor in patients undergoing colorectal surgery [14], renal cell carcinoma surgery, etc. [15]. However, almost no studies have investigated the predictive role of CAR for POD until now. Therefore, we hypothesized that CAR could serve as an effective predictor of POD after TJA. Material and Methods Patients This present study was approved by the Medical Institutional Ethics Committee of Zhejiang province. This single-center, observational, prospective study was performed in our hospital between March 2015 and March 2018. Elderly patients (aged 65~85 years) who were scheduled to undergo elective TJA with epidural anesthesia were consecutively recruited. Signed informed consent was required to offer for all the enrolled participants. The exclusion criteria were described as below: (1) with preexisting psychiatric (psychiatric, depression, etc.) or neurological (Parkinson's disease, myasthenia gravis, etc.) diseases; (2) with Alb infusion preoperatively; (3) with a preoperative condition of infection or liver cirrhosis which has a direct influence on the expressions of CRP and Alb; (4) with existing or preexisting dementia; (5) with a preoperative Minimental state examination (MMSE) score <24; (6) inability to cooperate (deafness, blindness, etc.); and (7) with uncompleted data or loss to follow-up. A total of 310 subjects were enrolled during this period, of which 38 were excluded according to the exclusion criteria (8 with psychiatric or neurological disease, 7 with Alb infusion preoperatively, 5 with a condition of infection, 4 with a MMSE score <24, 2 unable to cooperate, and 12 with missed data). Data Collection To exclude the potential influence of anesthesia on POD, all the included participants underwent TJA under epidural anesthesia by the same anesthesia team using the same narcotics (ropivacaine, lidocaine, etc.). Data collection included 3 aspects: (1) baseline characteristics including age, gender, body mass index, duration of education, smoking and drinking habits, preoperative comorbidities (hypertension, diabetes mellitus, etc.) and medications (statins, b-blockers, etc.), American Society of Anesthesiologists grade, and preoperative MMSE score; (2) operation-associated indexes including duration of surgery and anesthesia, postoperative recovery time, operation time, estimated blood loss, estimated blood loss, perioperative blood transfusion, and postoperative complications (surgical site infection, wound dehiscence, etc.); and (3) laboratory tests including CRP, Alb, etc. POD Evaluation An experienced psychiatrist who was blinded to this study protocol was consulted to confirm the diagnosis of POD. The definition of POD in this study was according to the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM V, 2013). POD assessment was performed daily within postoperative 7 days
(in the evening). The patients who had at least a positive POD diagnosis within 7 days after the operation were categorized into the POD group. Laboratory Tests Fasting peripheral venous blood samples were obtained preoperatively (at 6 AM 1 day before the surgery). Serum samples were then obtained through centrifugation at 3000 rpm for 10 min and stored at 80 C for laboratory tests. The serum expressions of inflammatory biomarkers, including tumor necrosis factor-a (TNF-a), CRP, and interleukin-6 (IL-6), were determined by enzyme-linked immunosorbent assay using kits (R&D Systems; Minneapolis, MN). Preoperative complete blood counts including hemoglobin, white blood cell, platelet, biochemical analyses including Alb, creatinine, and urea were also detected in the laboratory of our hospital. CAR was defined as preoperative CRP (mg/L)/preoperative Alb (g/dL). Statistical Analysis All the data were analyzed using GraphPad Prism 5.0 (GraphPad Inc, San Diego, CA) and SPSS 19.0 (SPSS Inc, Chicago, IL). Continuous data are presented as mean with standard error and analyzed by Mann-Whitney U test or t-test, while categorical data are presented as number (n, %) and analyzed by Chi-square test or Fisher exact test. Receiver operating characteristic curve analysis was utilized for evaluating the predictive and cut-off value of CAR for POD. Patients were categorized into high or low CAR groups according to the cut-off value. To screen potential risk factors for POD, binary univariate logistic regression analysis was performed, and only those factors with a P value < .1 were included into the final multivariate logistic regression model. A P value < .05 was considered statistically significant. Results Demographic and Clinical Data Of the total of 272 patients, the majority (157/272, 57.7%) were female patients. Among these enrolled patients, 152 (55.9%) underwent total hip arthroplasty and 120 (44.1%) underwent total knee arthroplasty. Within postoperative 7 days, there were 55 patients who had suffered POD with an incidence of 20.2% (55/272). The clinical characteristics of the patients with or without POD are present in Table 1. The percentage of heavy drinker was significantly higher in those with POD than in those without POD (P ¼ .021). An advanced age and a lower preoperative MMSE score were significantly associated with an increased risk of POD (P ¼ .009 and .047, respectively). The presence of preoperative comorbidities (diabetes and hypertension) and medications of bblockers were also associated with POD development (P ¼ .019, .036, and .025, respectively). The duration of operation (P ¼ .036) or anesthesia (P ¼ .020) was significantly higher in patients who suffered POD in comparison with those without POD. In addition, the estimated blood loss and perioperative blood transfusion rate were statistically higher in the POD group than the non-POD group (P ¼ .034 and .036, respectively). No significant difference was found in the gender distribution, education level, body mass index, American Society of Anesthesiologists physical status, smoking habits, types of operation, recovery time, the presence of hypercholesterolemia, peripheral vascular disease and history of myocardial infarct, preoperative medications of angiotensinconverting enzyme inhibitors, and statins between the patients with and without POD (P > .05). Moreover, there was also no close association between POD occurrence and other postoperative
J. Peng et al. / The Journal of Arthroplasty xxx (2019) 1e5 Table 1 Demographic and Clinical Data Associated With POD. Variables
Age (y) Gender, n (%) Male Female Education, n (%) High school >High school BMI (kg/m2) Preoperative MMSE score Active smoker, n (%) Heavy drinker, n (%) Preoperative comorbidities, n (%) Diabetes Hypercholesterolemia Hypertension Peripheral vascular disease History of myocardial infarct Preoperative medications, n (%) ACEIs b-blockers Statins ASA physical status, n (%) I-II III-IV Types of operation THA TKA Duration of surgery (min) Duration of anesthesia (min) Recovery time (min) Estimated blood loss (mL) Blood transfusion, n (%) Postoperative complications, n (%) Surgical site infection Wound dehiscence Dislocation Periprosthetic fracture Hematoma Deep vein thrombosis
Table 2 The Laboratory Tests and POD.
POD
P Value
Yes (n ¼ 55)
No (n ¼ 217)
74.5 ± 5.6
72.1 ± 6.1
22 (40.0) 33 (60.0)
93 (42.9) 124 (57.1)
36 (65.5) 19 (34.5) 22.3 ± 2.1 27.1 ± 1.5 7 (12.7) 13 (23.6)
128 (59.0) 89 (41.0) 22.1 ± 2.3 27.6 ± 1.7 23 (10.6) 25 (11.5)
12 9 15 5 6
(21.8) (16.4) (27.3) (9.1) (10.9)
22 36 33 17 23
(10.1) (16.6) (15.2) (7.8) (10.6)
8 (14.5) 11 (20.0) 7 (12.7)
26 (12.0) 20 (9.2) 30 (13.8)
34 (61.8) 21 (38.2)
150 (69.1) 67 (30.9)
28 (50.9) 27 (49.1) 117.4 ± 37.5 167.7 ± 40.1 40.7 ± 11.5 688.9 ± 134.6 14 (25.5)
124 (57.1) 93 (42.9) 107.3 ± 30.1 155.3 ± 33.7 40.3 ± 12.4 651.4 ± 113.4 30 (13.8)
5 3 3 2 4 5
(9.1) (5.5) (5.5) (3.6) (7.3) (9.1)
3
14 11 9 5 10 24
(6.5) (5.1) (4.1) (2.3) (4.6) (11.1)
Preoperative Laboratory Tests
POD
P Value
Yes (n ¼ 55) .009* .702 d d .381 d d .561 .047* .653 .021* d .019* .968 .036* .760 .947 d .608 .025* .832 .301 d d .406 d d .036* .020* .829 .034* .036* d .493 .908 .713 .577 .424 .673
P values were calculated by Chi-square test, Fisher exact test, ManneWhitney U-test or t-test. ASA, American Society of Anesthesiologists; ACEIs, angiotensin-converting enzyme inhibitors; BMI, body mass index; MMSE, Mini-Mental State Examination; POD, postoperative delirium; THA, total hip arthroplasty; TKA, total knee arthroplasty. * P value < .05.
complications (surgical site infection, wound dehiscence, etc.) in the elderly subjects after TJA (P > .05).
Hb (g/dL) WBC (109/L) PLT (109/L) IL-6 (pg/mL) TNF-a (nmol/L) Creatinine (mmol/L) Urea (mmol/L) CAR
11.5 7.1 217.6 17.9 8.2 85.2 6.6 2.9
± ± ± ± ± ± ± ±
1.9 2.4 37.5 7.1 2.1 16.7 1.7 0.8
No (n ¼ 217) 11.7 7.3 224.1 15.7 7.5 83.1 6.4 2.1
± ± ± ± ± ± ± ±
1.5 2.0 47.2 6.6 1.9 19.6 1.6 0.7
.405 .526 .344 .036* .018* .466 .414 <.001*
P values were calculated by Mann-Whitney U-test or t-test. POD, postoperative delirium; Hb, hemoglobin; PLT, platelet; WBC, white blood cell; IL-6, interleukin-6; TNF-a, tumor necrosis factor-a; CAR, C-reactive protein/albumin ratio. * P value < .05.
respectively (95% confidence interval [CI]: 0.737-0.872, P < .001). Based on the cut-off value of 2.35, patients were categorized into high CAR group (CAR 2.35) and low CAR (CAR < 2.35) group. Risk Factors for POD The binary univariate and multiple logistic regression analyses were performed to evaluate potential independent predictors for POD. As presented in Table 3, 13 possible risk factors (those factors with a P value < .05 in Tables 1 and 2) were subjected to the univariate logistic regression analysis. After that, 7 factors (age, preoperative medications of b-blockers, duration of surgery and anesthesia, preoperative levels of IL-6, TNF-a, and CAR) with a P value < .1 by univariate logistic analysis were enrolled into the final multivariate logistic regression model. As a result, age (odds ratio: 2.02, 95% CI: 1.03-3.96, P ¼ .038) and preoperative CAR level (odds ratio: 3.04, 95% CI: 1.23-7.23, P ¼ .016) were 2 independent risk factors for POD in elderly subjects undergoing TJA. Discussion Our results identified that increased age and preoperative CAR level were 2 independent risk factors for POD in elderly patients who underwent TJA. To our knowledge, this was the first study that highlighted the predictive role of preoperative CAR for POD. Our study has revealed the incidence of POD in elderly subjects after TJA
Laboratory Tests and POD The preoperative laboratory tests in patients with or without POD are shown in Table 2. The levels of blood cell counts (hemoglobin, white blood cell, and platelet) and biochemical analyses (creatinine and urea) did not differ significantly between patients with and without POD (P > .05). The serum expressions of IL-6 (P ¼ .036) and TNF-a (P ¼ .018) were observed to be higher in POD group than non-POD group. Furthermore, those patients who developed POD within postoperative 7 days also shown a significantly higher CAR (P < .001). Predictive Value of CAR for POD The predictive value of preoperative CAR for POD was evaluated by receiver operating characteristic curve analysis. As shown in Figure 1, the area under the curve of CAR for POD was 0.804, with the cut-off value of 2.35, a sensitivity of 66.82%, and a specificity of 80.00%,
Figure 1. The predictive value of CAR for POD by ROC curve analysis. The AUC of CAR for POD was 0.804, with the cut-off value of 2.35, a sensitivity of 66.82% and a specificity of 80.00%, respectively (95% CI: 0.737-0.872, P < .001). CAR, C-reactive protein/ albumin ratio; POD, postoperative delirium; AUC, area under the curve; ROC, receiver operating characteristic; CI, Confidence interval.
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Table 3 Risk Factors for POD by Univariate and Multiple Logistic Regression Analyses. Variables
Univariate Multivariate OR (95% CI)
Age (high vs low) Preoperative MMSE score (high vs low) Heavy drinker (yes vs no) Diabetes (yes vs no) Hypertension (yes vs no) Preoperative b-blockers (yes vs no) Duration of surgery (high vs low) Duration of anesthesia (high vs low) Estimated blood loss (high vs low) Blood transfusion (yes vs no) IL-6 (high vs low) TNF-a (high vs low) CAR (high vs low)
P Value OR (95% CI)
2.69 (1.37-5.53) .021 1.31 (0.74-2.32) .34
*
P Value
2.02 (1.03-3.96) .038*
0.94 (0.37-2.22) .84 1.02 (0.52-2.26) .79 1.36 (0.54-3.59) .52 1.83 (0.94-3.55) .081
1.81 (0.63-5.12) .24
2.44 (0.96-6.12) .059
2.32 (0.79-6.67) .13
1.81 (1.05-3.07) .029*
1.59 (0.94-2.61) .076
1.46 (0.86-2.51) .17 2.31 (0.78-7.14) .21 1.54 (0.92-2.57) .081 2.38 (0.94-5.91) .061 2.54 (1.27-5.06) .009*
1.51 (0.79-2.88) .21 1.43 (0.75-2.67) .28 3.04 (1.23-7.23) .016*
POD, postoperative delirium; MMSE, Mini-Mental State Examination; IL-6, interleukin-6; TNF-a, tumor necrosis factor-a; CAR, C-reactive protein/albumin ratio; CI, confidence interval; OR, odds ratio. * P value < .05.
to be 20.2% (55/272), which was quite in accordance with previous reports [5,6]. A positive correlation between POD and perioperative mortality has been indicated by recent studies [16], which emphasizes the importance of predicting POD effectively. Owing to the complicated and unclear pathogenesis of POD, it is a great change to reach an agreement regarding predicative factors for POD. Advanced age has been widely accepted as a well-established predictor for POD [17e19]. Our results from the multivariate logistic regression analysis also supported increased age as an independent risk factor for POD. A review by Inouye et al has identified an older age as a predisposing factor for POD [1], which strongly supports our results. For those elderly patients, gradual accumulation of permanent damage to dendrites, neurons, microglia, and receptors may make them more susceptible to delirium and cognitive impairment when biologically stressed [20,21]. A recent study has highlighted that preoperative CRP level is an independent risk factor for POD in elderly subjects after laparoscopic surgery for colon carcinoma [10]. Another study has also supported high-serum CRP concentrations preoperatively and on postoperative day 2 as potential predictors for POD in elderly patients after major elective noncardiac surgery [22]. However, whether preoperative CRP expression can serve as a predictor for POD still remains controversial in different cohort studies. Some previous studies have revealed the close association between Alb level and POD, and Alb is used as a continuous variable [23]. Preoperative hypoalbuminemia has been reported as a significant, independent predictive factor of POD in the patients hospitalized in an intensive care unit after cardiac surgery [24]. Moreover, some other studies have reported the predictive role of preoperative severe hypoalbuminemia (defined as serum Alb <30 g/L) for POD and worse outcomes in patients undergoing noncardiac surgery [25]. However, the classifications of hypoalbuminemia were different in different literatures, with the cut-off value ranging from 2.5 to 4.0 g/dL [13]. Increasing evidence has shown that postoperative poor outcomes closely correlate with the systemic inflammatory response following the operation stress, which was reflected by increased CRP and decreased Alb expressions [26,27]. CAR, taking 2
circulating acute phase proteins (CRP and Alb) into together, is an inflammation-based prognostic factor, and it can serve as a prognostic factor for patients with pancreatic cancer after pancreatic resection [28]. As suggested by a recent report, CAR can help to predict postoperative complications after colorectal surgery with a cut-off value of 2.2 [14]. CAR, a combination of CRP with Alb, is more likely to reflect the preexisting inflammation stress when comparing with CRP or Alb alone [14]. There is compelling evidence that the release of proinflammatory cytokines into the periphery and central nervous system plays a critically important role in the pathogenesis of POD [29,30]. The pathogenic role of systemic inflammation in POD may be a possible explanation for the predictive role of CAR for POD in this present study. To our knowledge, this was the first study that consider preoperative CAR as a predictor for POD in elderly subjects following TJA. This current study has some limitations. First, it is a singlecenter observational study with a relatively small sample size. Second, some residual confounding factors (such as sample selection bias, preoperative comorbidities, etc.) cannot be excluded completely. Third, this study only takes preoperative CAR into consideration, and the correlation between postoperative CAR and postoperative complications remains unclear. In addition, whether a combination of CAR with the other variables (IL-6, TNF-a, etc.) can be possible to predict risk for POD remains unclear and requires further studies to verify.
Conclusions In conclusions, preoperative CAR level may be a promising predictor for POD in elderly subjects following TJA. In our opinion, preoperative CAR evaluation may be beneficial to take prompt action before critical POD develops. The preoperative risk identification for POD will provide an opportunity to develop a targeted plan of intensive care focused on POD prevention. Considering the typically complex multifactorial etiology of POD, multicomponent nonpharmacologic risk factor approaches serve as the most effective strategy for POD prevention. A multicomponent intervention strategy for POD prevention through targeting risk factors for delirium was recommended. In our consideration, the interventions including reorientation, reduction of psychoactive medications, promoting sleep, nutritional support, and providing vision and hearing adaptations were recommended for those patients with high risks of POD.
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Preoperative C-Reactive Protein/Albumin Ratio, a Risk Factor for Postoperative Delirium in Elderly Patients After Total Joint Arthroplasty Jie Peng, MMBS, Guorong Wu, MMBS, Junping Chen, MMBS, Hui Chen, MMBS * Department of Anesthesiology, HwaMei Hospital, University of Chinese Academy of Sciences (Ningbo No.2 Hospital), Ningbo, Zhejiang Province, China
a r t i c l e i n f o
a b s t r a c t
Article history: Received 7 May 2019 Received in revised form 18 June 2019 Accepted 18 June 2019 Available online xxx
Background: Postoperative delirium (POD), as an acute brain failure, is widely reported as a very common postoperative complication, and it is closely associated with increased morbidity and mortality. This study aimed to investigate potential risk factors including C-reactive protein/albumin ratio (CAR) for POD in elderly subjects after total joint arthroplasty (TJA). Methods: A total of 272 elderly patients (aged 65~85 years) who were scheduled to undergo elective TJA with epidural anesthesia were consecutively recruited. The data of baseline characteristics, operationassociated indexes, and preoperative laboratory tests were collected. POD assessment was performed daily within postoperative 7 days. Receiver operating characteristic curve analysis was utilized for evaluating the predictive and cut-off value of CAR for POD. Risk factors for POD were evaluated by the binary univariate and multivariate logistic regression analyses. Results: Within postoperative 7 days, there were 55 patients who had suffered POD with an incidence of 20.2% (55/272). The area under the curve of CAR for POD was 0.804, with the cut-off value of 2.35, a sensitivity of 66.82%, and a specificity of 80.00%, respectively (95% confidence interval [CI]: 0.737-0.872, P < .001). Age (odds ratio: 2.02, 95% CI: 1.03-3.96, P ¼ .038) and preoperative CAR level (odds ratio: 3.04, 95% CI: 1.23-7.23, P ¼ .016) were 2 independent risk factors for POD in elderly subjects undergoing TJA. Conclusions: Preoperative CAR level may be a promising predictor for POD in elderly subjects following TJA. © 2019 Published by Elsevier Inc.
Keywords: total joint arthroplasty postoperative delirium C-reactive protein/albumin ratio risk factor biomarker
Postoperative delirium (POD), as an acute brain failure, is widely reported as a very common postoperative complication, and approximately, 50% of surgical patients have experienced POD [1].
Funding: The Key Program of Ningbo Natural Science Foundation, China (No. 2018A610216). Competing interests: None. Authors' contributions: J P and GR W participated in the conception and design, data collection, statistical analysis and wrote the manuscript. H C and JP C participated in the conception and design and data collection. No author associated with this paper has disclosed any potential or pertinent conflicts which may be perceived to have impending conflict with this work. For full disclosure statements refer to https://doi.org/10.1016/j.arth.2019.06.042. * Reprint requests: Hui Chen, MMBS, Department of Anesthesiology, HwaMei Hospital, University of Chinese Academy of Sciences (Ningbo No.2 Hospital), No.41 Xibei Road, Haishu District, Ningbo, Zhejiang Province, China. https://doi.org/10.1016/j.arth.2019.06.042 0883-5403/© 2019 Published by Elsevier Inc.
POD has become a crucial public health problem as it is closely associated with decreased life quality, prolonged hospital length of stay, increased morbidity, and mortality [2]. Numerous studies have demonstrated the detrimental impact of high POD severity on shortterm and long-term outcomes [3]. As described by previous studies, the incidence of POD varies from 15% to 53% in elderly surgical subjects [4]. A meta-analysis by Scott et al has revealed that the overall incidence of POD reaches as high as 17% in patients who underwent total joint arthroplasty (TJA) during hospital admission [5]. A prospective study by Chen et al has also reported a similar incidence of 16.5% after TJA [6]. However, the reported incidence of POD varies widely in different studies. Furthermore, to our knowledge, few wellestablished predictors have been outlined for POD incidence to date. Taken together, it is of great importance to determine potential independent risk factors for POD and risk stratification. C-reactive protein (CRP), an acute phase protein secreted by the liver and adipose tissue, is one of the most common biomarkers for
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systemic inflammation [7]. Some studies have indicated CRP as an independent risk factor for POD after hip surgery [8], vascular surgery, [9] and laparoscopic surgery for colon carcinoma [10]. Albumin (Alb), another circulating acute phase protein, is a frequently used parameter to assess the nutritional status of surgical patients [11]. Previous studies have shown that hypoalbuminemia is significantly associated with increased risks of postoperative complications including POD [12,13]. However, no consensus concerning the predictive role of CRP or Alb for POD has been made. The CRP/Alb ratio (CAR), a combination of CRP and Alb, has been suggested as a promising prognostic factor in patients undergoing colorectal surgery [14], renal cell carcinoma surgery, etc. [15]. However, almost no studies have investigated the predictive role of CAR for POD until now. Therefore, we hypothesized that CAR could serve as an effective predictor of POD after TJA. Material and Methods Patients This present study was approved by the Medical Institutional Ethics Committee of Zhejiang province. This single-center, observational, prospective study was performed in our hospital between March 2015 and March 2018. Elderly patients (aged 65~85 years) who were scheduled to undergo elective TJA with epidural anesthesia were consecutively recruited. Signed informed consent was required to offer for all the enrolled participants. The exclusion criteria were described as below: (1) with preexisting psychiatric (psychiatric, depression, etc.) or neurological (Parkinson's disease, myasthenia gravis, etc.) diseases; (2) with Alb infusion preoperatively; (3) with a preoperative condition of infection or liver cirrhosis which has a direct influence on the expressions of CRP and Alb; (4) with existing or preexisting dementia; (5) with a preoperative Minimental state examination (MMSE) score <24; (6) inability to cooperate (deafness, blindness, etc.); and (7) with uncompleted data or loss to follow-up. A total of 310 subjects were enrolled during this period, of which 38 were excluded according to the exclusion criteria (8 with psychiatric or neurological disease, 7 with Alb infusion preoperatively, 5 with a condition of infection, 4 with a MMSE score <24, 2 unable to cooperate, and 12 with missed data). Data Collection To exclude the potential influence of anesthesia on POD, all the included participants underwent TJA under epidural anesthesia by the same anesthesia team using the same narcotics (ropivacaine, lidocaine, etc.). Data collection included 3 aspects: (1) baseline characteristics including age, gender, body mass index, duration of education, smoking and drinking habits, preoperative comorbidities (hypertension, diabetes mellitus, etc.) and medications (statins, b-blockers, etc.), American Society of Anesthesiologists grade, and preoperative MMSE score; (2) operation-associated indexes including duration of surgery and anesthesia, postoperative recovery time, operation time, estimated blood loss, estimated blood loss, perioperative blood transfusion, and postoperative complications (surgical site infection, wound dehiscence, etc.); and (3) laboratory tests including CRP, Alb, etc. POD Evaluation An experienced psychiatrist who was blinded to this study protocol was consulted to confirm the diagnosis of POD. The definition of POD in this study was according to the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM V, 2013). POD assessment was performed daily within postoperative 7 days
(in the evening). The patients who had at least a positive POD diagnosis within 7 days after the operation were categorized into the POD group. Laboratory Tests Fasting peripheral venous blood samples were obtained preoperatively (at 6 AM 1 day before the surgery). Serum samples were then obtained through centrifugation at 3000 rpm for 10 min and stored at 80 C for laboratory tests. The serum expressions of inflammatory biomarkers, including tumor necrosis factor-a (TNF-a), CRP, and interleukin-6 (IL-6), were determined by enzyme-linked immunosorbent assay using kits (R&D Systems; Minneapolis, MN). Preoperative complete blood counts including hemoglobin, white blood cell, platelet, biochemical analyses including Alb, creatinine, and urea were also detected in the laboratory of our hospital. CAR was defined as preoperative CRP (mg/L)/preoperative Alb (g/dL). Statistical Analysis All the data were analyzed using GraphPad Prism 5.0 (GraphPad Inc, San Diego, CA) and SPSS 19.0 (SPSS Inc, Chicago, IL). Continuous data are presented as mean with standard error and analyzed by Mann-Whitney U test or t-test, while categorical data are presented as number (n, %) and analyzed by Chi-square test or Fisher exact test. Receiver operating characteristic curve analysis was utilized for evaluating the predictive and cut-off value of CAR for POD. Patients were categorized into high or low CAR groups according to the cut-off value. To screen potential risk factors for POD, binary univariate logistic regression analysis was performed, and only those factors with a P value < .1 were included into the final multivariate logistic regression model. A P value < .05 was considered statistically significant. Results Demographic and Clinical Data Of the total of 272 patients, the majority (157/272, 57.7%) were female patients. Among these enrolled patients, 152 (55.9%) underwent total hip arthroplasty and 120 (44.1%) underwent total knee arthroplasty. Within postoperative 7 days, there were 55 patients who had suffered POD with an incidence of 20.2% (55/272). The clinical characteristics of the patients with or without POD are present in Table 1. The percentage of heavy drinker was significantly higher in those with POD than in those without POD (P ¼ .021). An advanced age and a lower preoperative MMSE score were significantly associated with an increased risk of POD (P ¼ .009 and .047, respectively). The presence of preoperative comorbidities (diabetes and hypertension) and medications of bblockers were also associated with POD development (P ¼ .019, .036, and .025, respectively). The duration of operation (P ¼ .036) or anesthesia (P ¼ .020) was significantly higher in patients who suffered POD in comparison with those without POD. In addition, the estimated blood loss and perioperative blood transfusion rate were statistically higher in the POD group than the non-POD group (P ¼ .034 and .036, respectively). No significant difference was found in the gender distribution, education level, body mass index, American Society of Anesthesiologists physical status, smoking habits, types of operation, recovery time, the presence of hypercholesterolemia, peripheral vascular disease and history of myocardial infarct, preoperative medications of angiotensinconverting enzyme inhibitors, and statins between the patients with and without POD (P > .05). Moreover, there was also no close association between POD occurrence and other postoperative
J. Peng et al. / The Journal of Arthroplasty xxx (2019) 1e5 Table 1 Demographic and Clinical Data Associated With POD. Variables
Age (y) Gender, n (%) Male Female Education, n (%) High school >High school BMI (kg/m2) Preoperative MMSE score Active smoker, n (%) Heavy drinker, n (%) Preoperative comorbidities, n (%) Diabetes Hypercholesterolemia Hypertension Peripheral vascular disease History of myocardial infarct Preoperative medications, n (%) ACEIs b-blockers Statins ASA physical status, n (%) I-II III-IV Types of operation THA TKA Duration of surgery (min) Duration of anesthesia (min) Recovery time (min) Estimated blood loss (mL) Blood transfusion, n (%) Postoperative complications, n (%) Surgical site infection Wound dehiscence Dislocation Periprosthetic fracture Hematoma Deep vein thrombosis
Table 2 The Laboratory Tests and POD.
POD
P Value
Yes (n ¼ 55)
No (n ¼ 217)
74.5 ± 5.6
72.1 ± 6.1
22 (40.0) 33 (60.0)
93 (42.9) 124 (57.1)
36 (65.5) 19 (34.5) 22.3 ± 2.1 27.1 ± 1.5 7 (12.7) 13 (23.6)
128 (59.0) 89 (41.0) 22.1 ± 2.3 27.6 ± 1.7 23 (10.6) 25 (11.5)
12 9 15 5 6
(21.8) (16.4) (27.3) (9.1) (10.9)
22 36 33 17 23
(10.1) (16.6) (15.2) (7.8) (10.6)
8 (14.5) 11 (20.0) 7 (12.7)
26 (12.0) 20 (9.2) 30 (13.8)
34 (61.8) 21 (38.2)
150 (69.1) 67 (30.9)
28 (50.9) 27 (49.1) 117.4 ± 37.5 167.7 ± 40.1 40.7 ± 11.5 688.9 ± 134.6 14 (25.5)
124 (57.1) 93 (42.9) 107.3 ± 30.1 155.3 ± 33.7 40.3 ± 12.4 651.4 ± 113.4 30 (13.8)
5 3 3 2 4 5
(9.1) (5.5) (5.5) (3.6) (7.3) (9.1)
3
14 11 9 5 10 24
(6.5) (5.1) (4.1) (2.3) (4.6) (11.1)
Preoperative Laboratory Tests
POD
P Value
Yes (n ¼ 55) .009* .702 d d .381 d d .561 .047* .653 .021* d .019* .968 .036* .760 .947 d .608 .025* .832 .301 d d .406 d d .036* .020* .829 .034* .036* d .493 .908 .713 .577 .424 .673
P values were calculated by Chi-square test, Fisher exact test, ManneWhitney U-test or t-test. ASA, American Society of Anesthesiologists; ACEIs, angiotensin-converting enzyme inhibitors; BMI, body mass index; MMSE, Mini-Mental State Examination; POD, postoperative delirium; THA, total hip arthroplasty; TKA, total knee arthroplasty. * P value < .05.
complications (surgical site infection, wound dehiscence, etc.) in the elderly subjects after TJA (P > .05).
Hb (g/dL) WBC (109/L) PLT (109/L) IL-6 (pg/mL) TNF-a (nmol/L) Creatinine (mmol/L) Urea (mmol/L) CAR
11.5 7.1 217.6 17.9 8.2 85.2 6.6 2.9
± ± ± ± ± ± ± ±
1.9 2.4 37.5 7.1 2.1 16.7 1.7 0.8
No (n ¼ 217) 11.7 7.3 224.1 15.7 7.5 83.1 6.4 2.1
± ± ± ± ± ± ± ±
1.5 2.0 47.2 6.6 1.9 19.6 1.6 0.7
.405 .526 .344 .036* .018* .466 .414 <.001*
P values were calculated by Mann-Whitney U-test or t-test. POD, postoperative delirium; Hb, hemoglobin; PLT, platelet; WBC, white blood cell; IL-6, interleukin-6; TNF-a, tumor necrosis factor-a; CAR, C-reactive protein/albumin ratio. * P value < .05.
respectively (95% confidence interval [CI]: 0.737-0.872, P < .001). Based on the cut-off value of 2.35, patients were categorized into high CAR group (CAR 2.35) and low CAR (CAR < 2.35) group. Risk Factors for POD The binary univariate and multiple logistic regression analyses were performed to evaluate potential independent predictors for POD. As presented in Table 3, 13 possible risk factors (those factors with a P value < .05 in Tables 1 and 2) were subjected to the univariate logistic regression analysis. After that, 7 factors (age, preoperative medications of b-blockers, duration of surgery and anesthesia, preoperative levels of IL-6, TNF-a, and CAR) with a P value < .1 by univariate logistic analysis were enrolled into the final multivariate logistic regression model. As a result, age (odds ratio: 2.02, 95% CI: 1.03-3.96, P ¼ .038) and preoperative CAR level (odds ratio: 3.04, 95% CI: 1.23-7.23, P ¼ .016) were 2 independent risk factors for POD in elderly subjects undergoing TJA. Discussion Our results identified that increased age and preoperative CAR level were 2 independent risk factors for POD in elderly patients who underwent TJA. To our knowledge, this was the first study that highlighted the predictive role of preoperative CAR for POD. Our study has revealed the incidence of POD in elderly subjects after TJA
Laboratory Tests and POD The preoperative laboratory tests in patients with or without POD are shown in Table 2. The levels of blood cell counts (hemoglobin, white blood cell, and platelet) and biochemical analyses (creatinine and urea) did not differ significantly between patients with and without POD (P > .05). The serum expressions of IL-6 (P ¼ .036) and TNF-a (P ¼ .018) were observed to be higher in POD group than non-POD group. Furthermore, those patients who developed POD within postoperative 7 days also shown a significantly higher CAR (P < .001). Predictive Value of CAR for POD The predictive value of preoperative CAR for POD was evaluated by receiver operating characteristic curve analysis. As shown in Figure 1, the area under the curve of CAR for POD was 0.804, with the cut-off value of 2.35, a sensitivity of 66.82%, and a specificity of 80.00%,
Figure 1. The predictive value of CAR for POD by ROC curve analysis. The AUC of CAR for POD was 0.804, with the cut-off value of 2.35, a sensitivity of 66.82% and a specificity of 80.00%, respectively (95% CI: 0.737-0.872, P < .001). CAR, C-reactive protein/ albumin ratio; POD, postoperative delirium; AUC, area under the curve; ROC, receiver operating characteristic; CI, Confidence interval.
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Table 3 Risk Factors for POD by Univariate and Multiple Logistic Regression Analyses. Variables
Univariate Multivariate OR (95% CI)
Age (high vs low) Preoperative MMSE score (high vs low) Heavy drinker (yes vs no) Diabetes (yes vs no) Hypertension (yes vs no) Preoperative b-blockers (yes vs no) Duration of surgery (high vs low) Duration of anesthesia (high vs low) Estimated blood loss (high vs low) Blood transfusion (yes vs no) IL-6 (high vs low) TNF-a (high vs low) CAR (high vs low)
P Value OR (95% CI)
2.69 (1.37-5.53) .021 1.31 (0.74-2.32) .34
*
P Value
2.02 (1.03-3.96) .038*
0.94 (0.37-2.22) .84 1.02 (0.52-2.26) .79 1.36 (0.54-3.59) .52 1.83 (0.94-3.55) .081
1.81 (0.63-5.12) .24
2.44 (0.96-6.12) .059
2.32 (0.79-6.67) .13
1.81 (1.05-3.07) .029*
1.59 (0.94-2.61) .076
1.46 (0.86-2.51) .17 2.31 (0.78-7.14) .21 1.54 (0.92-2.57) .081 2.38 (0.94-5.91) .061 2.54 (1.27-5.06) .009*
1.51 (0.79-2.88) .21 1.43 (0.75-2.67) .28 3.04 (1.23-7.23) .016*
POD, postoperative delirium; MMSE, Mini-Mental State Examination; IL-6, interleukin-6; TNF-a, tumor necrosis factor-a; CAR, C-reactive protein/albumin ratio; CI, confidence interval; OR, odds ratio. * P value < .05.
to be 20.2% (55/272), which was quite in accordance with previous reports [5,6]. A positive correlation between POD and perioperative mortality has been indicated by recent studies [16], which emphasizes the importance of predicting POD effectively. Owing to the complicated and unclear pathogenesis of POD, it is a great change to reach an agreement regarding predicative factors for POD. Advanced age has been widely accepted as a well-established predictor for POD [17e19]. Our results from the multivariate logistic regression analysis also supported increased age as an independent risk factor for POD. A review by Inouye et al has identified an older age as a predisposing factor for POD [1], which strongly supports our results. For those elderly patients, gradual accumulation of permanent damage to dendrites, neurons, microglia, and receptors may make them more susceptible to delirium and cognitive impairment when biologically stressed [20,21]. A recent study has highlighted that preoperative CRP level is an independent risk factor for POD in elderly subjects after laparoscopic surgery for colon carcinoma [10]. Another study has also supported high-serum CRP concentrations preoperatively and on postoperative day 2 as potential predictors for POD in elderly patients after major elective noncardiac surgery [22]. However, whether preoperative CRP expression can serve as a predictor for POD still remains controversial in different cohort studies. Some previous studies have revealed the close association between Alb level and POD, and Alb is used as a continuous variable [23]. Preoperative hypoalbuminemia has been reported as a significant, independent predictive factor of POD in the patients hospitalized in an intensive care unit after cardiac surgery [24]. Moreover, some other studies have reported the predictive role of preoperative severe hypoalbuminemia (defined as serum Alb <30 g/L) for POD and worse outcomes in patients undergoing noncardiac surgery [25]. However, the classifications of hypoalbuminemia were different in different literatures, with the cut-off value ranging from 2.5 to 4.0 g/dL [13]. Increasing evidence has shown that postoperative poor outcomes closely correlate with the systemic inflammatory response following the operation stress, which was reflected by increased CRP and decreased Alb expressions [26,27]. CAR, taking 2
circulating acute phase proteins (CRP and Alb) into together, is an inflammation-based prognostic factor, and it can serve as a prognostic factor for patients with pancreatic cancer after pancreatic resection [28]. As suggested by a recent report, CAR can help to predict postoperative complications after colorectal surgery with a cut-off value of 2.2 [14]. CAR, a combination of CRP with Alb, is more likely to reflect the preexisting inflammation stress when comparing with CRP or Alb alone [14]. There is compelling evidence that the release of proinflammatory cytokines into the periphery and central nervous system plays a critically important role in the pathogenesis of POD [29,30]. The pathogenic role of systemic inflammation in POD may be a possible explanation for the predictive role of CAR for POD in this present study. To our knowledge, this was the first study that consider preoperative CAR as a predictor for POD in elderly subjects following TJA. This current study has some limitations. First, it is a singlecenter observational study with a relatively small sample size. Second, some residual confounding factors (such as sample selection bias, preoperative comorbidities, etc.) cannot be excluded completely. Third, this study only takes preoperative CAR into consideration, and the correlation between postoperative CAR and postoperative complications remains unclear. In addition, whether a combination of CAR with the other variables (IL-6, TNF-a, etc.) can be possible to predict risk for POD remains unclear and requires further studies to verify.
Conclusions In conclusions, preoperative CAR level may be a promising predictor for POD in elderly subjects following TJA. In our opinion, preoperative CAR evaluation may be beneficial to take prompt action before critical POD develops. The preoperative risk identification for POD will provide an opportunity to develop a targeted plan of intensive care focused on POD prevention. Considering the typically complex multifactorial etiology of POD, multicomponent nonpharmacologic risk factor approaches serve as the most effective strategy for POD prevention. A multicomponent intervention strategy for POD prevention through targeting risk factors for delirium was recommended. In our consideration, the interventions including reorientation, reduction of psychoactive medications, promoting sleep, nutritional support, and providing vision and hearing adaptations were recommended for those patients with high risks of POD.
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